Search ga_s2bm_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata\n\n(e.g. ‘epsg:32654’)\n:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n from:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n to (exclusive):

File format (GeoTiff, NetCDF):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider.\nFor Sentinel it is MGRS code.\n:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n to (exclusive):

Unique identifier for a datastrip relative to a given Datatake.\n\n(e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’)\n:

ESA product URI, with the '.SAFE' ending removed.\n\n(e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845')\n:

Granule ID according to the ESA naming convention\n\n(e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’)\n:

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2017-07-21 11:56:07	ga_s2bm_ard_3-2-1_50HLK_2017-07-21_final.stac-item
2017-08-20 11:49:42	ga_s2bm_ard_3-2-1_50JLQ_2017-08-20_final.stac-item
2017-10-06 11:40:29	ga_s2bm_ard_3-2-1_50HMJ_2017-10-06_final.stac-item
2017-10-12 12:02:35	ga_s2bm_ard_3-2-1_50JMT_2017-10-12_final.stac-item
2017-11-05 11:37:39	ga_s2bm_ard_3-2-1_50JML_2017-11-05_final.stac-item
2017-12-25 11:40:37	ga_s2bm_ard_3-2-1_50JPQ_2017-12-25_final.stac-item
2017-12-25 11:46:02	ga_s2bm_ard_3-2-1_50JML_2017-12-25_final.stac-item
2017-12-28 11:49:08	ga_s2bm_ard_3-2-1_50JNL_2017-12-28_final.stac-item
2018-01-24 11:37:42	ga_s2bm_ard_3-2-1_50HNH_2018-01-24_final.stac-item
2018-02-12 12:13:14	ga_s2bm_ard_3-2-1_49JGN_2018-02-12_final.stac-item
2018-03-24 12:13:16	ga_s2bm_ard_3-2-1_49KGR_2018-03-24_final.stac-item
2018-05-14 11:43:22	ga_s2bm_ard_3-2-1_50HMK_2018-05-14_final.stac-item
2018-06-06 11:51:08	ga_s2bm_ard_3-2-1_50JMN_2018-06-06_final.stac-item
2018-07-19 12:03:30	ga_s2bm_ard_3-2-1_49KGP_2018-07-19_final.stac-item
2018-08-02 11:44:54	ga_s2bm_ard_3-2-1_50HPK_2018-08-02_final.stac-item
2018-08-08 12:04:30	ga_s2bm_ard_3-2-1_50JLP_2018-08-08_final.stac-item
2018-09-07 12:02:58	ga_s2bm_ard_3-2-1_49KHR_2018-09-07_final.stac-item
2018-12-03 11:56:21	ga_s2bm_ard_3-2-1_50JLL_2018-12-03_final.stac-item
2019-01-08 12:13:53	ga_s2bm_ard_3-2-1_49KHR_2019-01-08_final.stac-item
2019-02-08 11:44:45	ga_s2bm_ard_3-2-1_50JRS_2019-02-08_final.stac-item
2019-02-14 12:04:31	ga_s2bm_ard_3-2-1_49KGP_2019-02-14_final.stac-item
2019-02-27 12:14:58	ga_s2bm_ard_3-2-1_49JFM_2019-02-27_final.stac-item
2019-03-19 12:14:40	ga_s2bm_ard_3-2-1_49JGN_2019-03-19_final.stac-item
2019-05-08 12:14:21	ga_s2bm_ard_3-2-1_49KGQ_2019-05-08_final.stac-item
2019-05-15 12:04:48	ga_s2bm_ard_3-2-1_50JLT_2019-05-15_final.stac-item
2019-06-11 11:55:28	ga_s2bm_ard_3-2-1_50JNQ_2019-06-11_final.stac-item
2019-06-21 11:55:57	ga_s2bm_ard_3-2-1_50JNN_2019-06-21_final.stac-item
2019-06-28 11:45:12	ga_s2bm_ard_3-2-1_50JQR_2019-06-28_final.stac-item
2019-07-11 11:56:13	ga_s2bm_ard_3-2-1_50JNM_2019-07-11_final.stac-item
2019-07-11 11:56:20	ga_s2bm_ard_3-2-1_50JLM_2019-07-11_final.stac-item
2019-07-21 11:56:13	ga_s2bm_ard_3-2-1_50JNM_2019-07-21_final.stac-item
2019-07-28 11:46:27	ga_s2bm_ard_3-2-1_50JPL_2019-07-28_final.stac-item
2019-07-31 11:56:33	ga_s2bm_ard_3-2-1_50JLL_2019-07-31_final.stac-item
2019-08-20 11:56:35	ga_s2bm_ard_3-2-1_50HNK_2019-08-20_final.stac-item
2019-08-27 11:46:47	ga_s2bm_ard_3-2-1_50HQJ_2019-08-27_final.stac-item
2019-10-22 12:05:16	ga_s2bm_ard_3-2-1_49JGL_2019-10-22_final.stac-item
2019-10-26 11:47:03	ga_s2bm_ard_3-2-1_50HPH_2019-10-26_final.stac-item
2019-11-25 11:46:34	ga_s2bm_ard_3-2-1_50HNK_2019-11-25_final.stac-item
2020-01-24 11:46:30	ga_s2bm_ard_3-2-1_50HNK_2020-01-24_final.stac-item
2020-04-09 12:04:39	ga_s2bm_ard_3-2-1_50JKT_2020-04-09_final.stac-item
2020-05-13 11:46:25	ga_s2bm_ard_3-2-1_50JML_2020-05-13_final.stac-item
2020-06-02 11:45:19	ga_s2bm_ard_3-2-1_50JQQ_2020-06-02_final.stac-item
2020-06-02 11:46:53	ga_s2bm_ard_3-2-1_50HNJ_2020-06-02_final.stac-item
2020-07-12 11:46:35	ga_s2bm_ard_3-2-1_50HPK_2020-07-12_final.stac-item
2020-07-18 12:05:42	ga_s2bm_ard_3-2-1_50JKP_2020-07-18_final.stac-item
2020-10-03 11:55:19	ga_s2bm_ard_3-2-1_50JPQ_2020-10-03_final.stac-item
2020-10-30 11:46:55	ga_s2bm_ard_3-2-1_50HNJ_2020-10-30_final.stac-item
2020-11-29 11:44:25	ga_s2bm_ard_3-2-1_50JRT_2020-11-29_final.stac-item
2021-01-14 12:05:29	ga_s2bm_ard_3-2-1_49JGK_2021-01-14_final.stac-item
2021-02-07 11:45:06	ga_s2bm_ard_3-2-1_50JPR_2021-02-07_final.stac-item
2021-03-09 11:46:29	ga_s2bm_ard_3-2-1_50HQK_2021-03-09_final.stac-item
2021-04-18 11:45:07	ga_s2bm_ard_3-2-1_50JNR_2021-04-18_final.stac-item
2021-05-24 12:05:08	ga_s2bm_ard_3-2-1_50JLR_2021-05-24_final.stac-item
2021-05-27 12:14:09	ga_s2bm_ard_3-2-1_49KHQ_2021-05-27_final.stac-item
2021-05-28 11:46:43	ga_s2bm_ard_3-2-1_50HQJ_2021-05-28_final.stac-item
2021-08-13 11:37:27	ga_s2bm_ard_3-2-1_50HNG_2021-08-13_final
2021-10-04 12:14:13	ga_s2bm_ard_3-2-1_49KGQ_2021-10-04_final.stac-item
2021-10-18 11:56:19	ga_s2bm_ard_3-2-1_50JNL_2021-10-18_final.stac-item
2021-11-27 11:56:18	ga_s2bm_ard_3-2-1_50JML_2021-11-27_final.stac-item
2022-02-15 11:55:58	ga_s2bm_ard_3-2-1_50JNM_2022-02-15_final.stac-item
2022-02-25 11:55:49	ga_s2bm_ard_3-2-1_50JMN_2022-02-25_final.stac-item
2022-03-01 11:36:59	ga_s2bm_ard_3-2-1_50HQH_2022-03-01_final.stac-item
2022-03-07 11:57:07	ga_s2bm_ard_3-2-1_50HLH_2022-03-07_final.stac-item
2022-03-13 12:13:53	ga_s2bm_ard_3-2-1_49KHR_2022-03-13_final.stac-item
2022-03-17 11:57:07	ga_s2bm_ard_3-2-1_50HLH_2022-03-17_final.stac-item
2022-03-27 11:55:07	ga_s2bm_ard_3-2-1_50JMR_2022-03-27_final.stac-item
2022-04-12 12:14:09	ga_s2bm_ard_3-2-1_49KGQ_2022-04-12_final.stac-item
2022-04-26 11:55:00	ga_s2bm_ard_3-2-1_50JNR_2022-04-26_final.stac-item
2022-06-22 11:46:17	ga_s2bm_ard_3-2-1_50JMM_2022-06-22_final.stac-item
2022-06-22 11:46:24	ga_s2bm_ard_3-2-1_50JPL_2022-06-22_final.stac-item
2022-07-01 12:13:59	ga_s2bm_ard_3-2-1_50KKA_2022-07-01_final.stac-item
2022-08-07 12:04:45	ga_s2bm_ard_3-2-1_49JGN_2022-08-07_final.stac-item
2022-08-14 11:56:29	ga_s2bm_ard_3-2-1_50JLL_2022-08-14_final.stac-item
2022-08-18 11:36:40	ga_s2bm_ard_3-2-1_50HPK_2022-08-18_final.stac-item
2022-08-24 11:56:11	ga_s2bm_ard_3-2-1_50JLM_2022-08-24_final.stac-item
2022-09-13 11:54:35	ga_s2bm_ard_3-2-1_50JPT_2022-09-13_final.stac-item
2022-09-13 11:55:51	ga_s2bm_ard_3-2-1_50JNN_2022-09-13_final.stac-item
2022-10-09 12:13:52	ga_s2bm_ard_3-2-1_49KHR_2022-10-09_final.stac-item
2022-12-19 11:44:44	ga_s2bm_ard_3-2-1_50JRS_2022-12-19_final.stac-item
2022-12-29 11:46:18	ga_s2bm_ard_3-2-1_50JPL_2022-12-29_final.stac-item
2023-01-24 12:04:40	ga_s2bm_ard_3-2-1_49JHN_2023-01-24_final.stac-item
2023-02-27 11:47:21	ga_s2bm_ard_3-2-1_50HNG_2023-02-27_final
2023-04-01 11:55:45	ga_s2bm_ard_3-2-1_50JLP_2023-04-01_final
2023-04-14 12:05:09	ga_s2bm_ard_3-2-1_50JLR_2023-04-14_final
2023-04-28 11:46:10	ga_s2bm_ard_3-2-1_50JNM_2023-04-28_final
2023-05-21 11:57:14	ga_s2bm_ard_3-2-1_50HLH_2023-05-21_final
2023-06-27 11:45:59	ga_s2bm_ard_3-2-1_50JNN_2023-06-27_final
2023-09-24 12:14:45	ga_s2bm_ard_3-2-1_49JGN_2023-09-24_final
2023-09-28 11:56:04	ga_s2bm_ard_3-2-1_50JLN_2023-09-28_final
2023-10-14 12:14:00	ga_s2bm_ard_3-2-1_49KGR_2023-10-14_final
2023-10-24 12:13:56	ga_s2bm_ard_3-2-1_49KHR_2023-10-24_final
2023-10-28 11:56:56	ga_s2bm_ard_3-2-1_50HLJ_2023-10-28_final
2023-11-14 11:46:43	ga_s2bm_ard_3-2-1_50HQJ_2023-11-14_final
2023-12-04 11:46:34	ga_s2bm_ard_3-2-1_50HNK_2023-12-04_final
2023-12-27 11:56:38	ga_s2bm_ard_3-2-1_50HMK_2023-12-27_final
2024-02-12 11:44:53	ga_s2bm_ard_3-2-1_50JPS_2024-02-12_final
2024-03-06 11:54:32	ga_s2bm_ard_3-2-1_50JNT_2024-03-06_final
2024-03-16 11:56:16	ga_s2bm_ard_3-2-1_50JNL_2024-03-16_final
2024-04-15 11:56:31	ga_s2bm_ard_3-2-1_50HNK_2024-04-15_final
2024-04-22 11:46:26	ga_s2bm_ard_3-2-1_50JML_2024-04-22_final

Return to ga_s2bm_ard_3 whole collection overview

ga_s2bm_ard_3: Geoscience Australia Sentinel 2B MSI Analysis Ready Data Collection 3

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

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